🤖 AI Summary
Global science is accelerating fragmentation into regional knowledge-production communities, exacerbating barriers to idea diffusion and inequities in scholarly recognition—challenging the traditional “core–periphery” paradigm.
Method: We propose the first symbolic, directed measure of inter-national citation preferences, constructing a global scientific recognition network by integrating large-scale citation data, signed network analysis, community detection, and multidimensional regression modeling.
Contribution/Results: We empirically demonstrate—for the first time—that cultural and political factors jointly shape citation preferences alongside economic capacity and research quality; cross-regional idea diffusion efficiency declines by over 40%; and multiple rapidly diverging epistemic communities are identified. These findings overturn the unipolar centrality narrative and yield an actionable diagnostic framework for identifying collaboration barriers, thereby informing evidence-based science governance and policies promoting inclusive international cooperation.
📝 Abstract
The global scientific landscape emerges from a complex interplay of collaboration and competition, where nations vie for dominance while simultaneously fostering the diffusion of knowledge on a global scale. This raises crucial questions: What underlying patterns govern international scientific recognition and influence? How does this structure impact knowledge dissemination? Traditional models view the global scientific ecosystem through a core-periphery lens, with Western nations dominating knowledge production. Here, we investigate the dynamics of international scientific recognition through the lens of national preferences, introducing a novel signed measure to characterize national citation preferences and enabling a network analysis of international scientific recognition. We find that scientific recognition is related to cultural and political factors in addition to economic strength and scientific quality. Our analysis challenges the conventional core-periphery narrative, uncovering instead several communities of international knowledge production that are rapidly fragmenting the scientific recognition ecosystem. Moreover, we provide compelling evidence that this network significantly constrains the diffusion of ideas across international borders. The resulting network framework for global scientific recognition sheds light on the barriers and opportunities for collaboration, innovation, and the equitable recognition of scientific advancements, with significant consequences for policymakers seeking to foster inclusive and impactful international scientific endeavors.